Wireless endoscopic capsules can transmit the picture of the inside of the digestive tract to the external receiver for the purpose of gastrointestinal diseases diagnose. The localization of the capsule is needed to correlate the picture of detected anomalies with the particular fragment of intestine. For this purpose, the analysis of wireless transmission parameters can be applied. Such methods are affected by the impact of the human body on the electromagnetic wave propagation that is specific to the anatomy of individual person. The article presents the algorithm of localization of endoscopic capsules with wireless transmitter based on the detection of phase difference of received signals. The proposed algorithm uses simplified human body models that can change their dielectric properties in each iteration to improve the location of the capsule endoscope. Such approach allows to reduce localization error by around 12 mm (15%) and can by used for patients of different physique without the need of the numerical models of individual body.
This work presents concepts of the use of algorithms inspired by the functions and properties of the nervous system in dense wireless networks. In particular, selected features of the brain consisting of a large number of nerve connections were analyzed, which is why they are a good model for a dense network. In addition, the action of a selected cells from the nervous system (such as neuron, microglia or astrocyte) as well as phenomena observed in it (e.g. neuroplasticity) are presented.
This article presents a consistent solution of Transmit Power Control in centralized (clustered) wireless network with and without jamming. Depending on the policy assumed, appropriate solutions are applied to minimize the power used in a system or to satisfy expected Quality of Service. Because of specific nature of the system there is no optimal solution which can be applied in practice. Correctness and effectiveness of four proposed Transmit Power Control algorithms was presented in the form of computer simulation results in which the system capacity, mean power used and the number of successful links were described.
The emerging potentials in the electronics field, which facilitate the creation of complex projects with innovative functionalities, while maintaining low costs, are becoming even more appreciated by designers and engineers. In this manuscript, a telemetry system was designed and realized for monitoring main parameters of a racing vehicle. A STM32 Nucleo board acquires data from sensors installed on vehicle and transmits them to a base station. Acquired data are both stored on a SD card and wirelessly transmitted, for ensuring robustness/reliability of operation. The carried out tests confirm the truthfulness and compatibility of acquired data related to the vehicle parameters.
The paper presents a circuit structure that can be used for powering an IoT (Internet of Things) sensor node and that can use energy just from its surroundings. The main advantage of the presented solution is its very low cost that allows mass applicability e.g. in the IoT smart grids and ubiquitous sensors. It is intended for energy sources that can provide enough voltage but that can provide only low currents such as piezoelectric transducers or small photovoltaic panels (PV) under indoor light conditions. The circuit is able to accumulate energy in a capacitor until a certain level and then to pass it to the load. The presented circuit exhibits similar functionality to a commercially available EH300 energy harvester (EH). The paper compares electrical properties of the presented circuit and the EH300 device, their form factors and costs. The EH circuit’s performance is tested together with an LTC3531 buck-boost DC/DC converter which can provide constant voltage for the following electronics. The paper provides guidelines for selecting an optimal capacity of the storage capacitor. The functionality of the solution presented is demonstrated in a sensor node that periodically transmits measured data to the base station using just the power from the PV panel or the piezoelectric generator. The presented harvester and powering circuit are compact part of the sensor node’s electronics but they can be also realized as an external powering module to be added to existing solutions.
In paper we present a case study of the radio dispatching communications for providing the voice service during mass events of the “Lednica 2000” Youth Meetings. The presentation is supported by over 20-year experience in organization of this event every year. We also describe a FM radio system deployed during this meeting for broadcasting the English translation.
The subject of the article is the design and practical implementation of the wireless mesh network. IQRF radio modules were used for the network design. The IQRF® technique has enabled the construction of a mesh network with the possibility of reconfiguration. The theoretical part contains a description of the IQRF® hardware solutions used. The practical scope includes the design part, where the configuration of the radio modules was carried out and the parameters of the radio network were set to allow its implementation in various topologies. Then, a wireless network consisting of 10 IQRF modules was launched in the P3 building of the Opole University of Technology. At this stage, configured radio modules were placed in selected rooms on all five floors of the building in order to carry out tests of the radio network constructed in this way. The tests included measuring the packet transmission delay time as well as the received signal strength. Research was carried out for several network topologies.
One of the ways to improve calculations related to determining the position of a node in the IoT measurement system is to use artificial neural networks (ANN) to calculate coordinates. The method described in the article is based on the measurement of the RSSI (Received Signal Strength Indicator), which value is then processed by the neural network. Hence, the proposed system works in two stages. In the first stage, RSSI coefficient samples are taken, and then the node location is determined on an ongoing basis. Coordinates anchor nodes (i.e. sensors with fixed and previously known positions) and the matrix of RSSI coefficients are used in the learning process of the neural network. Then the RSSI matrix determined for the system in which the nodes with unknown positions are located is fed into the neural network inputs. The result of the work is a system and algorithm that allows determining the location of the object without processing data separately in nodes with low computational performance.
This paper presents some construction analysis and test results of a Free Space Optics system operating at the wavelength of 9.35 μm. In the system, a quantum cascade laser and a photoreceiver with mercury cadmium telluride photodetectors were used. The main parameters of these elements were discussed taking into account a data link operation. It also provides to determine a data range for various weather conditions related to scattering and scintillation. The results of numerical analyses defined the properties of currently available FSO technologies working in the near infrared or in the short infrared range of spectrum versus the performances of the developed system. The operation of this system was verified in three different test environments. The obtained results may also contain important issues related to the practical application of any FSO system.